2017 7th IEEE International Conference on System Engineering and Technology (ICSET)最新文献_第4页

Texture analysis and classification in ultrasound medical images for determining echo pattern characteristics 超声医学图像中回波模式特征的纹理分析与分类

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123414

H. A. Nugroho, M. Rahmawaty, Yuli Triyani, I. Ardiyanto, L. Choridah, Reni Indrastuti

{"title":"Texture analysis and classification in ultrasound medical images for determining echo pattern characteristics","authors":"H. A. Nugroho, M. Rahmawaty, Yuli Triyani, I. Ardiyanto, L. Choridah, Reni Indrastuti","doi":"10.1109/ICSENGT.2017.8123414","DOIUrl":"https://doi.org/10.1109/ICSENGT.2017.8123414","url":null,"abstract":"Ultrasound is one of the imaging modalities commonly used for detecting mass abnormalities of nodule. The observation of ultrasound images is conducted by the radiologists, which tend to be subjective. Therefore, the use of computer aided diagnosis (CADx) system based on image processing can assist the radiologists to give more objective decision-making for detecting the mass abnormalities of nodule. This study proposes an approach to identify echo pattern characteristic of nodule by analysing some extracted texture features. A total of 343 ultrasound images consisting of 191 solid and 152 cystic nodules are used in this study. Three classifiers, namely Naïve Bayes, support vector machine (SVM) and multilayer perceptron (MLP) classifier are involved to measure the performance of proposed approach. Generally, MLP classifier achieves the best performance in classifying nodule with the accuracy of 93.00%, Kappa of 0.86 and AUC of 0.974. These results show that the proposed approach successfully identifies echo pattern characteristic of cystic and solid nodules on the ultrasound images.","PeriodicalId":350572,"journal":{"name":"2017 7th IEEE International Conference on System Engineering and Technology (ICSET)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129818321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Multi-priority based QoS MAC protocol for wireless sensor networks 基于多优先级的无线传感器网络QoS MAC协议

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123420

Sohail Sarang, M. Drieberg, A. Awang

{"title":"Multi-priority based QoS MAC protocol for wireless sensor networks","authors":"Sohail Sarang, M. Drieberg, A. Awang","doi":"10.1109/ICSENGT.2017.8123420","DOIUrl":"https://doi.org/10.1109/ICSENGT.2017.8123420","url":null,"abstract":"Wireless Sensor Networks (WSNs) have gained significant attention due to their wide range of applications. In these networks, the sensor nodes collect different types of data from the surrounding environment. There are many applications that require sensor node to transmit urgent data packets faster than normal data packets. In the literature, most of the available medium access control (MAC) protocols have not considered quality-of-service (QoS) and have not addressed multi-priority of the data packets. In this paper, a multi-priority based MAC protocol is proposed, which provides QoS in WSNs, called MPQ-MAC protocol. In the MPQ-MAC protocol, a novel technique is proposed to reduce the delay and energy consumption in the network. Furthermore, the performance of the MPQ-MAC protocol has been evaluated in terms of average delay for priority data packets, energy consumption per node, packet delay, network throughput and packet delivery ratio using Castalia simulator. Simulation results show that the proposed protocol reduces the delay for priority data packet of up to 46.5% and energy consumption per node of up to 1.7% while maintaining network throughput and packet delivery ratio in the network.","PeriodicalId":350572,"journal":{"name":"2017 7th IEEE International Conference on System Engineering and Technology (ICSET)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128944037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Comparing statistical classifiers for emotion classification 比较情感分类的统计分类器

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123443

Raseeda Hamzah, N. Jamil, K. A. Samah, Nur Nabilah Abu Mangshor, Nurbaity Sabri, Rosniza Roslan

引用次数: 5

Design and implementation of attitude stabilization on Ganefly flapping wings micro aerial vehicle using Paparazzi 基于Paparazzi的Ganefly扑翼微型飞行器姿态稳定设计与实现

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123445

M. A. Nugroho, A. Sepri, R. Benyamin, B. Trilaksono, Agoes Moelyadi

{"title":"Design and implementation of attitude stabilization on Ganefly flapping wings micro aerial vehicle using Paparazzi","authors":"M. A. Nugroho, A. Sepri, R. Benyamin, B. Trilaksono, Agoes Moelyadi","doi":"10.1109/ICSENGT.2017.8123445","DOIUrl":"https://doi.org/10.1109/ICSENGT.2017.8123445","url":null,"abstract":"Flapping Wings Micro Aerial Vehicle (FWMAV) is developed from MAV (Micro Aerial Vehicle) technology, which uses flapping wing mechanism to fly rather than rotors. MAV itself is a branch of UAV (Unmanned Aerial Vehicle) technology, and focuses on minimizing size and weight of the aircraft. Ganefly is an FWMAV with capability to fly autonomously based on GPS readings and waypoints input from the user. This autopilot system works in conjunction with other parts of the control systems in Ganefly, which also includes attitude stabilization system. Ganefly uses yaw control loop for horizontal attitude stabilization, because Ganefly does not use aileron to control roll, unlike usual aircrafts. The stabilization system is implemented using standard PID control and Paparazzi UAV firmware, on a Lisa/S autopilot board. Testing for stabilization system was done in Manual and Stabilization mode, and testing for autopilot mode was done in Autopilot mode. Results gathered from testing indicate that Ganefly in its flight is not horizontally stable in both Manual and Stabilization mode, and thus was not able to be tested on Autopilot mode.","PeriodicalId":350572,"journal":{"name":"2017 7th IEEE International Conference on System Engineering and Technology (ICSET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124031550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Design and implementation of Pan-Tilt control for face tracking 面向人脸跟踪的泛倾斜控制的设计与实现

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123449

S. R. Yosafat, C. Machbub, E. Hidayat

引用次数: 16

Variable hysteresis current controller with fuzzy logic controller based induction motor drives 可变磁滞电流控制器采用模糊逻辑控制器驱动感应电机

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123432

N. Farah, M. Talib, Z. Ibrahim, S. S. M. Isa, J. M. Lazi

引用次数: 15

Educational game as interactive learning for hurricane safety 飓风安全教育游戏互动学习

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123447

Mohammad Syahmi Rosli, Nur Nabilah Abu Mangshor, Nurbaity Sabri, Z. Ibrahim

引用次数: 3

A hybrid feature selection model for text clustering 文本聚类的混合特征选择模型

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123411

A. Alsaeedi, M. A. Fattah, Khalid S. Aloufi

引用次数: 3

Fault detection in quadrotor MAV 四旋翼微型飞行器故障检测

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123422

C. Jing, Dwi Pebrianti, Goh Ming Qian, L. Bayuaji

{"title":"Fault detection in quadrotor MAV","authors":"C. Jing, Dwi Pebrianti, Goh Ming Qian, L. Bayuaji","doi":"10.1109/ICSENGT.2017.8123422","DOIUrl":"https://doi.org/10.1109/ICSENGT.2017.8123422","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) is being used in a wide range of human life. Researcher preferred quadrotor as it can be brought into the first generation of simulator map of an aircraft. It can be developed into larger manned flight. In this regard, extensive research in Fault detection (FD) is necessary, so that it can enhance its safety features. FD is designed to respond and to exclude the wrong information and to quickly perceive and shoulder important regulation. The proposed method for the fault detection in this study uses hybrid technique which combines the Kalman filter and Artificial Neural Network (ANN). Two classes of approaches are analyzed: the system identification approach using ANN and the observer-based approach using Kalman filter. A representative Artificial Neural Network (ANN) model has been designed and used to simulate the system behaviors under various failure conditions. The Kalman filter recognizes data from sensors and indicates the fault of the system in sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. The information will then be fed to ANN, which consists of a bank of parameter estimation that generates failure state. The result of the residual signal before filtered and after filtered showed that Kalman-ANN is able to identify multi fault and immediately correct the system to the normal state. The accuracy of the detection is 85 percent. The proposed method is able to detect fault in a short time with delay of 9.23E-05 seconds.","PeriodicalId":350572,"journal":{"name":"2017 7th IEEE International Conference on System Engineering and Technology (ICSET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122315947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Prediction of photovoltaic system output using hybrid least square support vector machine 基于混合最小二乘支持向量机的光伏系统输出预测

2017 7th IEEE International Conference on System Engineering and Technology (ICSET) Pub Date : 2017-10-01 DOI: 10.1109/ICSENGT.2017.8123437

M. Aziz, Z. M. Yasin, Z. Zakaria

{"title":"Prediction of photovoltaic system output using hybrid least square support vector machine","authors":"M. Aziz, Z. M. Yasin, Z. Zakaria","doi":"10.1109/ICSENGT.2017.8123437","DOIUrl":"https://doi.org/10.1109/ICSENGT.2017.8123437","url":null,"abstract":"The electrical system photovoltaic (PV) modules required special design considerations due to unpredictable and sudden changes in weather conditions such as the solar irradiation level as well as the cell operating temperature. Therefore, this study presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm — Least Square Support Vector Machine (CS-LSSVM). Available historical output power data are analyzed and appropriate features are selected for the model. There are two inputs vectors to the model consists of solar irradiation and ambient temperature. Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for better prediction performance. The performance of CS-LSSVM is compared with those obtained from LS-SVM using cross-validation technique in terms of accuracy. In this paper, Mean Absolute Percentage Error (MAPE) is used to quantify the performance of the prediction. Besides that, evaluation also carried out by calculating the correlation of determination. The historical PV data is utilized to validate the workability of the proposed technique. The results showed that CS-LSSVM provides better performance in predicting photovoltaic system power output.","PeriodicalId":350572,"journal":{"name":"2017 7th IEEE International Conference on System Engineering and Technology (ICSET)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132545286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8